McDonald’s China Adopts Operations Research for Network Design

Shouwei Tang (), Lei Wang (), Yun Shi (), Andy Li (), Kevin Lin (), Chen Xiang (), Sophia Niu (), Shaofeng Zhou (), Ming Liu () and Hank Tang ()
Additional contact information
Shouwei Tang: Optimization Analytics Technology Pte. Ltd., Singapore 199591
Lei Wang: Optimization Analytics Technology Pte. Ltd., Singapore 199591
Yun Shi: McDonald’s China, Shanghai 201103, China
Andy Li: McDonald’s China, Shanghai 201103, China
Kevin Lin: Xianhui Logistics, Shanghai 201801, China
Chen Xiang: Optimization Analytics Technology Pte. Ltd., Singapore 199591
Sophia Niu: Optimization Analytics Technology Pte. Ltd., Singapore 199591
Shaofeng Zhou: Optimization Analytics Technology Pte. Ltd., Singapore 199591
Ming Liu: Xianhui Logistics, Shanghai 201801, China
Hank Tang: Xianhui Logistics, Shanghai 201801, China

Interfaces, 2025, vol. 55, issue 1, 36-47

Abstract: The supply chain network design (SCND) problem is a typical optimization problem that determines the structure of a supply chain and affects its costs and operational performance. SCND deals with various decisions, such as determining the number, size, and location of facilities and the optimal material and product flows of the entire supply chain network. Therefore, SCND is one of the most crucial planning problems in supply chain management. In this paper, we present a practical approach in which we adopt a mixed-integer programming (MIP) mathematical model to solve a real industry SCND problem for McDonald’s China. As a result of this project, McDonald’s China has saved millions of dollars in logistics costs and reduced CO 2 emissions by more than 10%. In our approach, size-reduction techniques were successfully applied to deal with a large-scale model, making it possible to analyze hundreds of scenarios before coming to a consensus.

Keywords: network design; supply chain optimization; large-scale MILP model; mathematical modeling; Edelman award (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:inm:orinte:v:55:y:2025:i:1:p:36-47

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